The devil isn't always in the details: how system properties can inform ecology

Selection on stability across ecological scales. Jonathan J. Borrelli, Stefano Allesina, Priyanga Amarasekare, Roger Arditi, Ivan Chase, John Damuth, Robert D. Holt, Dmitrii O. Logofet, Mark Novak, Rudolf P. Rohr, Axel G. Rossberg, Matthew Spencer, J. Khai Tran, Lev R. Ginzburg. 2015. Trends in Ecology & Evolution, http://dx.doi.org/10.1016/j.tree.2015.05.001.

This paper in TREE  on selection at higher level systems has been on my must-read list since it came out a few weeks ago, and it was worth the wait. It does what the best TREE papers do - makes you think a bit more deeply about a common topic. In this case, it develops an approach to understanding complex ecological systems (communities, ecosystems) that is blind to the details that ecologists often focus on.

The search for generalities and commonalities drives modern ecology. In short (though this paper deserves an in-depth read), this paper argues that we can learn much by considering stability and feasibility in complex ecological systems. That is, we can also study community structure or trophic webs by considered whether specific configurations of the system are stable. This is in contrast to a context-centric study of a system, where the usual list of proximate causes (productivity, niche availability, connectivity, etc, etc) may be used to understand why the system looks as it does.

The authors' premise is that nonadaptive (e.g. unstable) ecological systems will be unfavourable and selected against, and the resulting selective process “can produce many of those recurrent ecological patterns that have been observed in nature over large scales of space and time.” This requires that you accept a few underlying concepts: first, that large scale systems also experience selection (whether one prefers selection be in parentheses is up to the reader), in that unstable systems will be lost at faster rates leading to greater frequency of stable systems; and second, that this process of selection is determined by the properties of the system alone, not the specific conditions ecologists often focus on.

As an illustration, consider four possible food webs depicting intraguild predation that vary in their interaction strengths. All configurations are possible, but A-C are likely to lead to exclusion of the intraguild predator. D is most likely to be stable since the strong interaction between the resource and prey results in negative feedbacks between the densities of all species (i.e. when the resource is low, the prey should also be low, reducing the predator density as well) and thus more likely to be observed in natural systems. 

From Borrelli et al 2015.

A more specific example looks at attack rates and handling times in predator-prey interactions. When stability is considered, it seems that although predator-prey cycles may occur, it should be uncommon to have such extreme oscillations that populations reach dangerously low levels where stochastic extinctions may occur. Data suggests that oscillatory dynamics are less common in predator-prey relationships, but do occur particularly for specialist predator/prey pairings. Theory (Rosenzweig-MacArthur predator-prey models) predict that such pairings should be most stable if prey are weakly self-limited and predators have high attach rates/long handling times. Empirical evidence for this prediction supports it surprisingly well.

From Borrelli et al 2015.

 
Other related approaches consider feasibility across food webs, communities, and ecosystems. A community perspective might consider interactions across all species, perhaps using a network approach. Networks should tend towards formations that are the most stable – e.g. short chains rather than long ones. The commonness of nested network structures may reflect these constraints. 

Such an approach to ecology is not entirely new (Robert May's weak interactions comes to mind). But it provides perhaps the best potential explanation I’ve seen for ‘generality’ focused approaches in ecology, including ecological allometric relationships, macroevolutionary patterns, and network approaches. Macroecological patterns have often captured, rather than tidy linear relationships, occupied versus unoccupied parameter space. Thinking about feasibility as a macroecological ‘mechanism’ for ecological patterns at the system scale might lead to new research directions. 

Why pattern-based hypotheses fail ecology: the rise and fall of ecological character displacement

Yoel E. Stuart, Jonathan B. Losos, Ecological character displacement: glass half full or half empty?, Trends in Ecology & Evolution, Available online 26 March 2013

Just as ecology is beginning to refocus on integrating evolutionary dynamics and community ecology, a paper from Yoel Stuart and Jonathan Losos (2013) suggests that perhaps the best-known eco-evolutionary hypothesis - Ecological Character Displacement (ECD) – needs to be demoted in popularity. They review the existing evidence for ECD and in the process illustrate the rather typical path that research into pattern-based hypotheses seems to be taking.

ECD developed during that period of ecology when competition was at the forefront of ecological thought. During the 1950s-1960s, Connell, Hutchinson and McArthur produced their influential ideas about competitive coexistence. At the same time, Brown and Wilson (1956) first described ecological character displacement. ECD is defined as involving first, competition for limited resources; second, in response, selection for resource partitioning which drives populations to diverge in resource use. Ecological competition drives adaptive evolution in resource usage – either resulting in exaggerated divergence in sympatry or trait overdispersion. ECD fell in line with a competition-biased worldview, integrated ecology and evolution, and so quickly became entrenched: the ubiquity of trait differences between sympatric species seemed to support its predictions. Pfennig and Pfennig (2012) go so far as to say ‘Character displacement...plays a key, and often decisive, role in generating and maintaining biodiversity.’

One problem was that tests of ECD tended to make it a self-fulfilling prophecy. Differences in resource usage are expected when coexisting species compete; therefore if differences in resource usage are observed, competition is assumed to be the cause. In the ideal test, divergent sympatric species would be found experimentally to compete, and ECD could be used to explain the proximal cause of divergence. But the argument was also made that when divergent sympatric species were not found to compete, this was also evidence of ECD, since “ghosts of competition past” could have lead to complete divergence such that competition no longer occurred. This made it rather difficult to disprove ECD.

There was pushback in the 1970s against these problems, but interestingly, ECD didn’t fall out of favour. A familiar pattern took form: initial ecstatic support, followed by critical papers, which were in turn rebutted by new experimental studies. Theoretical models both supported or rebutted the hypothesis depending on the assumptions involved. In response the large literature, several influential reviews were written (Schluter (2000), Dayan and Simberloff (2005)) that appeared to suggest at least partial support for the ECD from existing data. Rather than dimming interest in ECD, debate kept it relevant for 40+ years. And continued relevance translated to the image of ECD as a longstanding (hence important) idea. Stuart and Losos carry out a new evaluation of the existing evidence for ECD using Schluter and McPhail’s (1992) ‘6 criteria’, using both the papers from the two previous reviews and more recent studies. Their results suggest that strong evidence for ECD is nearly non-existent, with only 5% of all 144 studies meeting all 6 criteria. (Note: this isn't equivalent to suggesting that ECD is nearly non-existent, just that currently support is limited. There's a good discussion as to some of the possible reasons that ECD has been rarely observed, in the paper).

From Stuart and Losos (2013). Fraction of cases from Schluter 2000, Dayan and Simberloff 2005, and this study that meet either 4 or all 6 of the criteria for ECD.

The authors note that there are many explanations for this finding of weak support: the study of evolution in nature is difficult, particularly given the dearth of long term studies. The 6 criteria are very difficult to fulfill. But they also make an important, much more general point: character displacement patterns can result from multiple processes that are not competition, so patterns on their own are not indicative. Patterns that result from legitimate ecological character displacement may not show the predicted trait overdispersion. The story of the rise and fall of ECD is a story with applications to many pattern-driven ecological hypotheses. There are many axiomatic relationships you learn about in introductory courses: productivity-diversity hump shaped relationships, the intermediate disturbance hypothesis, ECD, etc, etc. These have guided hypothesis formation and testing for 40 years and have become entrenched in the literature despite criticism. And similarly, there are recent papers suggesting that long-standing pattern-based hypotheses are actually wrong or at least misguided (e.g. 1, 2, 3, etc). Why? Because pattern-driven hypotheses lack mechanism, usually relying on some sort of common-sense description of a relationship. The truth is that the same pattern may result from multiple processes. Further, a single process can produce multiple patterns. So a pattern means very little without the appropriate context.

So have we wasted 40 years of time, energy and resources jousting at windmills? Probably not, data and knowledge are arrived at in many ways. And observing patterns is important - it is the source of information from natural systems we use to develop hypotheses. But it is hopeful that this is a period where ecology is recognizing that pattern-based hypotheses (and particularly the focus on patterns as proof for these hypotheses) ask the right questions but focus on the wrong answers.

Long-term studies of Darwin's finches have provided strong evidence for ECD.

Progress on the problem of pattern, process and scale

Jérôme Chave. 2013. The problem of pattern and scale in ecology: what have we learned in 20 years? Ecology Letters. DOI: 10.1111/ele.12048.

Why do patterns get so much attention from ecologists? MacArthur (1972) suggested it was because patterns imply repetition, and repetition implies predictability. And prediction is the Holy Grail of ecology. Of course, patterns are meaningless without consideration of spatial or temporal scale. As Levin put it in his MacArthur lecture (1992) "the description of pattern is the description of variation, and the quantification of variation requires the determination of scales". Observing, modelling, and predicting ecological patterns at differing spatial scales has dominated much of ecological thought since Levin’s paper – today, entire subfields heavily focus on patterns through space or time (species-area relationships, macroecology, biogeography, etc).

When ecological research focuses on pattern, but lacks attention to process and scale, it has received much (deserved) criticism. Even when patterns are considered at the appropriate scale and with regard to process, the ability to understand how these processes and patterns translate from one scale to the next (i.e. how do we explain the differing relationship between invasion success and community diversity at local compared to regional scales?) is still limited. And yet clearly connecting processes across scales is a central goal. In the upcoming issue of Ecology Letters, a review article by Jérôme Chave looks at how ecology has progressed in dealing with patterns and scale in the last 20 years.

Chave does a great job of placing current ecological thought into historical context. Sometimes we forget that one of the benefits of ecology’s youth is that ecology has developed concurrently with necessary technological advancements and demand for ecological knowledge. As a result, the need for ecological knowledge and the ability to provide it are tightly linked in time. As a result, Chave suggests that ecology is making noticeable progress, particularly in four focal areas: 1) coupling ecology and evolution, 2) global change, 3) modularity in interaction networks, and 4) spatial patterns of diversity.

The first two topics reflect ongoing issues in ecology. The incorporation of evolutionary dynamics into ecology is an increasingly popular topic (for example), and it is not uncommon for ecological and evolutionary dynamics to have similar temporal scales. Explaining temporal patterns then may require coupling models of ecology and evolution: for example a study of Darwin’s finches found that for one period evolutionary dynamics were occurring on a more rapid temporal scales than ecological dynamics. Global change has dominated ecological research and the problem of scaling processes up from local to global or from global to local effects (of temperature on productivity, etc) is another clear area of growth. This may be the most successful attempts to scale, since models of global carbon cycles have progressed from empirical data and models to predictive models. An apparent example of what can be achieved when demand and appropriate technology are both present.

The remaining two foci relate to networks, and spatial patterns of diversity. The first, modularity in interaction networks, allows groups of interactions to be incorporated into larger scale networks; for individual variation could be incorporated into interactions between species. More generally, Chave suggests that the “abstracted multidimensional space of an interaction network” might be one way to simplify temporal and spatial scales. He suggests that this is where ecology could learn from other studies of complex biological systems such as cellular networks and networks of human governance and management. Finally, spatial patterns of diversity – a striking and oft-considered issue in ecology – are suggested as an area in ecology that has seen advances. Biological diversity is patchy through space, and the amount of patchiness is dependent on the scale of observation. Planktonic blooms might be patchy on a global scale while tropical trees might be patchy over meters. Scaling from local patterns to global has been difficult – for example, models of local dispersal don’t necessarily predict regional dispersal patterns. Chave suggests that one problem in the past was the ignorance of processes at larger scales (i.e. systematics, biogeography) and a predominant focus is on local processes. He provides a few examples that have bridged this issue, for example neutral theory includes both regional and local processes, while ecophylogenetics incorporates evolutionary history.

The review focuses attention on several relevant or insightful approaches to the problem of pattern and scale, and suggests possible connections between ecology and other areas of work (for example, interaction networks and metabolic networks). Although it provides interesting examples, it offers little synthesis or ideas for reconciling issues of pattern and scale, and while the four foci are valid and appropriate, they feel like a rather patchy way of covering a larger and more general issue. This may simply be too complicated and large a topic to cover in a single short review. Chave seems a little generous is giving props to approaches which at their best do incorporate multiple scales (e.g. neutral theory and ecophylogenetics), but which arguably have relied heavily on pattern analyses without a strong focus on process, something that seems to go against the spirit of the review. In addition, some of the explicitly general attempts to reconcile scale and pattern in community ecology are missing. For example, a series of papers from Brett Melbourne and Peter Chesson used 'scale transition theory' to model dynamics across multiple scales. This framework has been applied at least to a few fisheries-related papers. In addition, research on predator-prey dynamics has long considered the question of how functional responses scale up (one review). That said, it's clear that ecology has made progress in some areas and that there are options for moving forward.

Ultimately, Chave seems to suggest that the question of how well ecology can deal with patterns and scale depends on whether complexity is reducible or intrinsic to understanding natural systems. He goes so far as to state “This suggests that in approaching novel frontiers of the study of complex ecological systems we need to pause about the challenge ahead of us...Once we enter the realm of complex systems, neither physics nor biology are well equipped to progress.” This is obviously a pessimistic take on the future for ecology. Is it true?